Enterprise Multi-Agent AI System Design
A production-ready design for web and mobile AI assistants using multi-agent orchestration, RAG, MCP tool execution, guardrails, human approval, observability, and evaluation.
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Practical AI engineering, live products, architecture examples, and books — organized in one place.
Production multi-agent design, orchestration, tools, and operations for real-world AI workflows.
A production-ready design for web and mobile AI assistants using multi-agent orchestration, RAG, MCP tool execution, guardrails, human approval, observability, and evaluation.
Open resourceLangChain and LangGraph platform with specialized agents, tool integration, RAG, workflow state, HITL, and an interactive visual workflow demo.
Open resourceLive Smart Agent demo plus enterprise AI agent architecture — design layers, reasoning loop, use cases, and production best practices.
Open resourceInteractive hub explaining tools in agentic AI workflows, tool execution loops, and sandboxed tool-call simulation.
Open resourceEnterprise deep dive into how data becomes the environment autonomous agents operate in.
Open resourceHuman-in-the-loop patterns for secure, aligned AI — action approval, risk boundaries, and production control.
Open resourceProduction control plane for agentic workflows — observability, tracing, evaluation, monitoring, alerts, and cost management.
Open resourceRetrieval systems and enterprise LLM patterns for accurate, grounded, production-ready applications.
Interactive enterprise RAG pipeline — hybrid retrieval, permission filtering, reranking, grounding validation, and production query simulation.
Open resourceLLM architecture, agentic patterns, RAG, fine-tuning, governance, security, structured outputs, tool calling, streaming, and HITL.
Open resourceReal production architectures and interview-ready system-design playbooks from shipped systems.
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Open resourceInterview-ready Google ADK / GCP agent system design mock — playbook, HealthNet HIPAA scenario, regulated finance scenario, and edge-case answers.
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A practical guide to designing, deploying, and operating production-ready AI systems — agents, RAG, MCP, A2A, and the full system-design lifecycle.
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